Assessing a numerical cellular braided‐stream model with a physical model
Bibliographic record
Abstract
Abstract A. B. Murray and C. Paola (1994, Nature, vol. 371, pp. 54–57; 1997, Earth Surface Processes and Landforms, vol. 22, pp. 1001–1025) proposed a cellular model for braided river dynamics as an exploratory device for investigating the conditions necessary for the occurrence of braiding. The model reproduces a number of the general morphological and dynamic features of braided rivers in a simplified form. Here we test the representation of braided channel morphodynamics in the Murray–Paola model against the known characteristics (mainly from a sequence of high resolution digital elevation models) of a physical model of a braided stream. The overall aim is to further the goals of the exploratory modelling approach by first investigating the capabilities and limitations of the existing model and then by proposing modifications and alternative approaches to modelling of the essential features of braiding. The model confirms the general inferences of Murray and Paola (1997) about model performance. However, the modelled evolution shows little resemblance to the real evolution of the small‐scale laboratory river, although this depends to some extent on the coarseness of the grid used in the model relative to the scale of the topography. The model does not reproduce the bar‐scale topography and dynamics even when the grid scale and amplitude of topography are adapted to be equivalent to the original Murray–Paola results. Strong dependence of the modelled processes on local bed slopes and the tendency for the model to adopt its own intrinsic scale, rather than adapt to the scale of the pre‐existing topography, appear to be the main causes of the differences between numerical model results and the physical model morphology and dynamics. The model performance can be improved by modification of the model equations to more closely represent the water surface but as an exploratory approach hierarchical modelling promises greater success in overcoming the identified shortcomings. Copyright © 2005 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".